Predictive AI Models for Dermatological and Systemic Complications and Their Impact on Gastrointestinal Health in Post-Surgical and Traumatology Recovery

Abstract

Predictive artificial intelligence (AI) models have become transformative tools in anticipating dermatological and systemic complications that affect postoperative recovery, particularly in gastrointestinal health. These AI-driven models leverage extensive clinical, imaging, and biometric data to detect early signs of adverse events such as infections, abnormal wound healing, and systemic inflammatory responses. In the clinical realm of surgery and traumatology, AI enhances diagnostic precision, supporting personalized patient management and timely therapeutic interventions. The integration of AI facilitates continuous monitoring and prognostic evaluation, which significantly contributes to reducing postoperative morbidity related to dermatological and gastrointestinal complications. Moreover, these models assist in optimizing surgical outcomes by predicting patient-specific risks, thereby refining decision-making processes and rehabilitation protocols. This technology also holds promise in improving understanding of the interplay between skin-related complications and gastrointestinal health, which is critical for holistic patient recovery. By harnessing machine learning algorithms, clinicians are equipped to identify high-risk cases earlier and tailor interventions that promote faster and safer recuperation. This review synthesizes recent advances in AI predictive modeling pertinent to dermatological and systemic complications in postoperative care, emphasizing their impact on gastrointestinal health during recovery. It also highlights challenges and future directions for integrating AI ethically and effectively into clinical practice to improve outcomes in surgical and trauma patients